Publication: Modeling and optimization of G-protein coupled receptor signal transduction
2
Issued Date
2011-06-01
Resource Type
ISSN
09720871
Other identifier(s)
2-s2.0-79959870353
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Far East Journal of Mathematical Sciences. Vol.53, No.1 (2011), 17-33
Suggested Citation
Charin Modchang, Busayamas Pimpunchat, Wannapong Triampo, Darapond Triampo, Yongwimon Lenbury Modeling and optimization of G-protein coupled receptor signal transduction. Far East Journal of Mathematical Sciences. Vol.53, No.1 (2011), 17-33. Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/12144
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Title
Modeling and optimization of G-protein coupled receptor signal transduction
Abstract
Signal transduction is the process by which a cell converts one kind of signal or stimulus into another. In this process, G-protein coupled receptors (GPCRs) are considered a major class of membrane protein receptors. GPCRs play a critical role in signal transduction, and they are important pharmacological drug targets. Motivated by some specific experimental data, we construct a mathematical model to investigate a signaling system of interest. The model is composed of mass-action ordinary differential equations that describe ligand-receptor and receptor- G-protein interactions. Because the kinetic reaction rates in the signaling processes previously gathered in reliable in vivo and in vitro experiments are limited to a small number of known values, we apply a genetic algorithm (GA) to estimate the parameter values in our model. In order to carry out the parameter estimation, we use the Augmented Lagrangian Genetic Algorithm (ALGA) with help from the mathematical theorem of infinite norm. This method ensures a faster parameter estimation speed in the modeled system. In addition, mathematical analyses are also performed. Some good agreement between analytic, numerical and experimental data was found. The simulation results of the model are extensively discussed and compared with the experimental data. © 2011 Pushpa Publishing House.